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非线性拟合结合交叉参考的迭代虹膜定位方法

Iris Iterative Location Using Nonlinear Data Fitting and Cross-reference

  • 摘要: 首先利用虹膜边缘数据拟合虹膜的初始形状参数;然后参考拟合误差的大小舍弃随机噪声与边缘毛刺,再进行新的迭代拟合,直到拟合平均误差收敛到设定门限以下;最后利用标准Hough变换进行小范围精确定位.仿真实验结果表明:文中提出的算法的性能优于现有文献报道的虹膜定位算法,稳定性、速度和精度已经达到较高程度.

     

    Abstract: The initial shape parameters were obtained first by using all edge pixels of iris, then discarding non-edge data iteratively according to the error of each subsequent fitting. New data were refined again and again until the average fitting error is under the defined threshold. Finally, the iris center and radius are decided accurately in a small scope by using standard Hough transform. Comparative simulation results show that the performance of speed and robustness is improved as compared to the existing methods.

     

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